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  • 22 - Dealing with Repeated Measures

  • from Part IV - Understanding What Your Data Are Telling You About Psychological Processes
  • Edited by Harry T. Reis, University of Rochester, New York, Tessa West, New York University, Charles M. Judd, University of Colorado Boulder
  • Book:
    Handbook of Research Methods in Social and Personality Psychology
    Published online:
    12 December 2024
    Print publication:
    19 December 2024, pp 532-564

  • Summary

    Over-time, repeated measures, or longitudinal data are terms referring to repeated measurements of the same variables within the same unit (e.g., person, family, team, company). Longitudinal data come from many sources, including self-reports, behaviors, observations, and physiology. Researchers collect repeated measures for a variety of reasons, such as wanting to model change in a process over time or wanting to increase measurement reliability. Whatever the reason for data collection, longitudinal methods pose unique challenges and opportunities. This chapter has three main goals: (1) to help researchers consider design decisions when developing a longitudinal study, (2) to describe the different decisions researchers have to make when analyzing longitudinal data, and (3) to consider the unique properties of longitudinal designs that researchers should be aware of when designing and analyzing longitudinal studies. We aim to provide a comprehensive overview of the major issues that researchers should consider, and we also point to more extensive resources.